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There are very interesting improvements to SQL, which are much more ergonomic, extend functionality, and provide higher-level abstractions. Also backward compatible. PRQL and Malloy immediately come to mind but there are more. Anybody has good explanations why they struggle to get wide adoption?

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When it comes to data stack tooling, organizations aren't always optimizing for a better way to do things as much as minimizing the worst possible scenario.

New syntax is nice, but it means that analysts and engineers need to learn something new and are more likely to make mistakes that could bubble up to production. There's always an argument to be made why shiny new tool XYZ is better, but unless it's 100X better, organizations are reluctant to switch from something like vanilla PostgreSQL that they know works 100% of the time.

Normally I would agree, except for the fact that this system works by converting PRQL to SQL. So it's not 100% throwing out the baby with the bath water, since there there are still means for newer engineers to learn SQL through this tooling!

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